1. Field of the Invention
The present invention relates to a video camera system, and, more particularly, to an apparatus for providing camera position data, including pan, tilt and zoom position data, for use in video content analysis.
2. Description of the Related Art
There are numerous known video surveillance systems which may be used to track a moving object such as a person or vehicle. Some such systems utilize a fixed camera having a stationary field of view (FOV). To fully cover a given surveillance site with a fixed camera system, however, it will oftentimes be necessary to use a significant number of fixed cameras.
Movable cameras which may pan, tilt and/or zoom may also be used to track objects. The use of a PTZ (pan, tilt, zoom) camera system will typically reduce the number of cameras required for a given surveillance site and also thereby reduce the number and cost of the video feeds and system integration hardware such as multiplexers and switchers associated therewith. Control signals for directing the pan, tilt, zoom movements typically originate from a human operator via a joystick or from an automated video tracking system.
A problem is that, in processing the images being acquired by the video camera, it is often necessary to ascertain the field of view of each image with a high degree of accuracy, and virtually in real time. For example, when applying a mask to the acquired images, it is important to maintain the mask in position over the objects to be masked throughout pan, tilt and zoom camera movements which may constantly change the field of view of the camera. The use of privacy masks and virtual masks is disclosed in U.S. patent application Ser. No. 11/199,762, entitled VIRTUAL MASK FOR USE IN AUTOTRACKING VIDEO CAMERA IMAGES, filed on Aug. 9, 2005, which is hereby incorporated by reference herein. Automated video tracking is another application in which it may be necessary to keep track of the field of view of the camera. More particularly, in order to determine the magnitude and direction of movement of an object of interest that is being tracked, it may be necessary to account for changes in the field of view of the camera from image to image. For example, changes in the field of view may make it appear that an object of interest is moving from image to image, when in fact it is not.
Corner matching is a conventional technique for identifying stationary objects in acquired images and deriving the change of the field of view from changes in the location of the stationary object from image to image. More particularly, a corner of a stationary object, or an entire stationary object, may be located in sequentially acquired images, and changes in the field of view of the camera between the two images may be derived from changes in the location and possibly size of the stationary object between the two images. A problem is that corner matching is computationally intensive, and diverts processing power from other video content analysis. Another problem is that the success of corner matching depends upon the content of the FOV. In particular, it requires stationary object(s) to be present in the FOV.
What is needed in the art is a video system capable of ascertaining changes in the field of view of the camera essentially in real time, and without performing corner matching.